Lightwaves improve brain tumor surgery

First-of-its-kind research shows promise for developing a method to clearly identify cancerous tissue during surgery. These findings may potentially improve outcomes for those undergoing surgery to remove glioblastoma multiforme (GBM), a tumor that attacks tissue around nerve cells in the brain. GBM is a type of brain tumor that is both common and deadly.

"Even with intensive treatment, including surgical removal of as much cancerous tissue as is currently possible combined with radiation and chemotherapy, the prognosis for GBM patients remains dismal," said lead author Steven N. Kalkanis, MD, a neurosurgeon and codirector at Henry Ford's Hermelin Brain Tumor Center in Detroit, Michigan. The study was published in the Journal of Neuro-Oncology (2014; doi:10.1007/s11060-013-1326-9).

"For now, their average life expectancy is around 12 to 18 months," said Kalkanis. GBM poses a particular problem for the surgeon. Some tumors have clearly defined edges, or margins, that differentiate it from normal brain tissue, whereas GBM margins are diffuse, blending into healthy tissue. This leaves the neurosurgeon uncertain about successfully finding and removing the entire malignancy.

The scientists set out to develop a highly accurate, efficient, and inexpensive tool to distinguish normal brain tissue from both GBM and necrotic (dead) tissue rapidly, in real time, in the operating room.

The researchers chose Raman spectroscopy, which measures scattered light to provide a wavelength signature for the material being studied. The developer, Indian physicist Sir C.V. Raman, won the 1930 Nobel Prize for Physics, and his spectroscopy has been used to remotely test industrial pollution in smokestack plumes, among other widely varied applications. Recent advances have shrunk the technology and sped up its processing.

"We decided to take full advantage of these advancements, which lend themselves exceptionally well to a small, portable hand-held device, potentially yielding immediate results in real-time. When developed, it would be the first of its kind in the world for this sort of brain tumor application," said Kalkanis.

Using 40 frozen sections of GBM-riddled brain tissue, the team aimed to develop a database of normal brain matter, GBM, and necrotic tissue as identified by Raman spectroscopy, as well as a statistical analysis algorithm for providing rapid diagnosis of tumor margins during brain surgery.

After creating and testing their method, the researchers were able to distinguish the three types of tissue with up to 99.5% accuracy. Normal brain tissue was found to have increased lipid content, necrotic tissue had increased protein and nucleic acid content, and GMB tissue fell somewhere in between the two. Using frozen samples did lead to artifacts that slightly lowered the accuracy on some samples because of the formation of ice crystals.

"But because we are developing these techniques to be used on live tissue during surgery, freeze artifact should not be a significant confounding factor," Kalkanis said.